DOI QR코드

DOI QR Code

A Long-term Monitoring Demonstration of Smart Home System for the Elderly

노인을 위한 스마트 홈 시스템 장기 모니터링 실증 연구

  • 이지헌 (고려대학교 미래건설환경융합연구소) ;
  • 차승현 (한국과학기술원 문화기술대학원)
  • Received : 2021.08.16
  • Accepted : 2021.09.27
  • Published : 2021.09.30

Abstract

A smart home system improves the elderly's quality of life by monitoring and analyzing their movements and health conditions with better health-care and social support services. Therefore, there has been an effort to adopt a smart home system for the independently living elderly. However, to the best of our knowledge, no study has investigated the usability of a smart home system on actual independently living elderly housing in long-term settings. Thus, this study aims to demonstrate the usability of a smart home system on independently living elders in living lab conditions. The BLE smart band and the BLE receiver were chosen for the smart home system to monitor the movement of the participants in their homes as well as to monitor the heart rates, step counts, sleep index. Nine independent living elderly from the senior welfare center in Kimjae participated in this living lab demonstration experiment for ten months. This demonstration experiment confirmed the effectiveness of low-cost and easily adoptable IoT-based BLE sensor sets on independent living elders and discussed the troubles and limitations of the experiment. By grasping the pros and cons of IoT-based BLE sensor sets, this study seeks to improve the accessibility and usability of smart home systems for the elderly population in independent living arrangements.

Keywords

Acknowledgement

본 연구는 대한민국 교육부와 한국연구재단의 연구비 지원 (NRF-2019S1A5A2A03038527)에 의해 수행되었습니다.

References

  1. Adibi, S. (2012). Link technologies and BlackBerry mobile Health (mHealth) solutions: A review. IEEE Transactions on Information Technology in Biomedicine, 16(4), pp. 586-597. https://doi.org/10.1109/TITB.2012.2191295
  2. Alam, M. R., Reaz, M. B. I., Ali, M. A. M. (2012). A review of smart homes - Past, present, and future. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 42(6), pp. 1190-1203. https://doi.org/10.1109/TSMCC.2012.2189204
  3. Alirezaie, M., Renoux, J., Kockemann, U., Kristoffersson, A., Karlsson, L., Blomqvist, E., Tsiftes, N., Voigt, T., Loutfi, A. (2017). An ontology-based context-aware system for smart homes: E-care@home. Sensors, 17(7).
  4. Anwar, Y. A., White, W. B. (1998). Chronotherapeutics for Cardiovascular Disease. Drugs, 55, pp. 631-643. https://doi.org/10.2165/00003495-199855050-00003
  5. Askenasy, J. J. M., Goldstein, R. (1995). Environment and Sleep Does a Subtropical Climate Imply a Seasonal Rhythm in REM Sleep? Sleep, 18(10), pp. 895-900. https://doi.org/10.1093/sleep/18.10.895
  6. Awais, M., Chiari, L., Ihlen, E. A. F., Helbostad, J. L., Palmerini, L. (2019). Physical Activity Classification for Elderly People in Free-Living Conditions. IEEE Journal of Biomedical and Health Informatics, 23(1), pp. 197-207. https://doi.org/10.1109/jbhi.2018.2820179
  7. Aznar-Gimeno, R., Labata-Lezaun, G., Adell-Lamora, A., Abadia-Gallego, D., del-Hoyo-Alonso, R., Gonzalez-Munoz, C. (2021). Deep Learning for Walking Behaviour Detection in Elderly People Using Smart Footwear. Entropy, 23(6), pp. 777. https://doi.org/10.3390/e23060777
  8. Bae, I. H. (2014). An ontology-based approach to ADL recognition in smart homes. Future Generation Computer Systems, 33, pp. 32-41. https://doi.org/10.1016/j.future.2013.04.004
  9. Barger, T. S., Brown, D. E., Alwan, M. (2005). Health-status monitoring through analysis of behavioral patterns. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans., 35(1), pp. 22-27. https://doi.org/10.1109/TSMCA.2004.838474
  10. Belmonte-Fernandez, O., Puertas-Cabedo, A., Torres-Sospedra, J., Montoliu-Colas, R., Trilles-Oliver, S. (2017). An indoor positioning system based on wearables for ambient-assisted living. Sensors, 17(1), pp. 36. https://doi.org/10.3390/s17010036
  11. Bijnen, F. C. H., Feskens, E. J. M., Caspersen, C. J., Mosterd, W. L., Kromhout, D. (1998). Age, Period, and Cohort Effects on Physical Activity Among Elderly Men During 10 Years of Follow-up: The Zutphen Elderly Study. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 53A(3), pp. M235-M241. https://doi.org/10.1093/gerona/53A.3.M235
  12. Blankevoort, C. G., Van Heuvelen, M. J., Boersma, F., Luning, H., De Jong, J., Scherder, E. J. (2010). Review of effects of physical activity on strength, balance, mobility and ADL performance in elderly subjects with dementia. Dementia and geriatric cognitive disorders, 30(5), pp. 392-402. https://doi.org/10.1159/000321357
  13. Borg, C., Hallberg, I. R., Blomqvist, K. (2006). Life satisfaction among older people (65+) with reduced self-care capacity: the relationship to social, health and financial aspects. Journal of Clinical Nursing, 15(5), pp. 607-618. https://doi.org/10.1111/j.1365-2702.2006.01375.x
  14. Brown, C. J., Markusson, N. (2019). The responses of older adults to smart energy monitors. Energy Policy, 130, pp. 218-226. https://doi.org/10.1016/j.enpol.2019.03.063
  15. Cepeda, M., Koolhaas, C. M., van Rooij, F. J. A., Tiemeier, H., Guxens, M., Franco, O. H., Schoufour, J. D. (2018). Seasonality of physical activity, sedentary behavior, and sleep in a middle-aged and elderly population: The Rotterdam study. Maturitas, 110, pp. 41-50. https://doi.org/10.1016/j.maturitas.2018.01.016
  16. Chan, M., Esteve, D., Escriba, C., Campo, E. (2008). A review of smart homes-Present state and future challenges. Computer Methods and Programs in Biomedicine, 91(1), pp. 55-81. https://doi.org/10.1016/j.cmpb.2008.02.001
  17. Chintalapudi, K., Padmanabha Iyer, A., Padmanabhan, V. N. (2010). Indoor localization without the pain. Proceedings of the Sixteenth Annual International Conference on Mobile Computing and Networking - MobiCom '10, pp. 173-184.
  18. Chung, J., Donahoe, M., Schmandt, C., Kim, I.-J., Razavai, P., Wiseman, M. (2011). Indoor location sensing using geo-magnetism. Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services - MobiSys '11, pp. 141-154.
  19. Daher, M., Diab, A., El Badaoui El Najjar, M., Ali Khalil, M., Charpillet, F. (2017). Elder Tracking and Fall Detection System Using Smart Tiles. IEEE Sensors Journal, 17(2), pp. 469-479. https://doi.org/10.1109/JSEN.2016.2625099
  20. Dawadi, P. N., Cook, D. J., Schmitter-Edgecombe, M., Parsey, C. (2013). Automated assessment of cognitive health using smart home technologies. Technology and Health Care, 21(4), pp. 323-343. https://doi.org/10.3233/THC-130734
  21. Deedwania, P. C. Nelson, J. R. (1990). Pathophysiology of silent myocardial ischemia during daily life. Hemodynamic evaluation by simultaneous electrocardiographic and blood pressure monitoring. Circulation, 82(4), pp. 1296-1304. https://doi.org/10.1161/01.CIR.82.4.1296
  22. Demiris, G., Hensel, B. K., Skubic, M., Rantz, M. (2008). Senior residents' perceived need of and preferences for "smart home" sensor technologies. International Journal of Technology Assessment in Health Care, 24(1), pp. 120-124. https://doi.org/10.1017/S0266462307080154
  23. DeQuattro, V., Lee, D. D., Allen, J., Sirgo, M., Plachetka, J. (1988). Labetalol blunts morning pressor surge in systolic hypertension. Hypertension, 11(2_pt_2).
  24. Dew, M. A., Hoch, C. C., Buysse, D. J., Monk, T. H., Begley, A. E., Houck, P. R., Hall, M., Kupfer, D. J., Reynolds, C. F. (2003). Healthy Older Adults' Sleep Predicts All-Cause Mortality at 4 to 19 Years of Follow-Up. Psychosomatic Medicine, 65(1), pp. 63-73. https://doi.org/10.1097/01.PSY.0000039756.23250.7C
  25. Donaldson, G. C., Robinson, D., Allaway, S. L. (1997). An analysis of arterial disease mortality and BUPA health screening data in men, in relation to outdoor temperature. Clinical Science, 92(3), pp. 261-268. https://doi.org/10.1042/cs0920261
  26. Dorsey, C. M., Teicher, M. H., Cohen-Zion, M., Stefanovic, L., Satlin, A., Tartarini, W., Harper, D., Lukas, S. E. (1999). Core Body Temperature and Sleep of Older Female Insomniacs Before and After Passive Body Heating. Sleep, 22(7), pp. 891-898. https://doi.org/10.1093/sleep/22.7.891
  27. Ehn, M., Eriksson, L. C., Akerberg, N., Johansson, A. C. (2018). Activity monitors as support for older persons' physical activity in daily life: Qualitative study of the users' experiences. JMIR mHealth uHealth, 6.
  28. Ehrenhard, M., Kijl, B., Nieuwenhuis, L. (2014). Market adoption barriers of multi-stakeholder technology: Smart homes for the aging population. Technological Forecasting and Social Change, 89, pp. 306-315. https://doi.org/10.1016/j.techfore.2014.08.002
  29. Fang, Y. M., Chang, C. C. (2016). Users' psychological perception and perceived readability of wearable devices for elderly people. Behaviour and Information Technology, 35(3), pp. 225-232. https://doi.org/10.1080/0144929X.2015.1114145
  30. Farina, N., Sherlock, G., Thomas, S., Lowry, R. G., Banerjee, S. (2019). Acceptability and feasibility of wearing activity monitors in community-dwelling older adults with dementia. International Journal of Geriatric Psychiatry, 34(4), pp. 617-624. https://doi.org/10.1002/gps.5064
  31. Fernandez-Llatas, C., Benedi, J. M., Garcia-Gomez, J. M., Traver, V. (2013). Process mining for individualized behavior modeling using wireless tracking in nursing homes. Sensors, 13(11), pp. 15434-15451. https://doi.org/10.3390/s131115434
  32. Giebel, C. M., Sutcliffe, C., Stolt, M., Karlsson, S., Renom-Guiteras, A., Soto, M., Verbeek, H., Zabalegui, A., Challis, D. (2014). Deterioration of basic activities of daily living and their impact on quality of life across different cognitive stages of dementia: A European study. International Psychogeriatrics, 26(8), pp. 1283-1293. https://doi.org/10.1017/s1041610214000775
  33. Goodwin, J., Pearce, V. R., Taylor, R. S., Read, K. L. Q., Powers, S. J. (2001). Seasonal cold and circadian changes in blood pressure and physical activity in young and elderly people. Age and Ageing, 30(4), pp. 311-317. https://doi.org/10.1093/ageing/30.4.311
  34. Hall, A., Boulton, E., Stanmore, E. (2019). Older adults' perceptions of wearable technology hip protectors: implications for further research and development strategies. Disability and Rehabilitation: Assistive Technology, 14(7), pp. 663-668. https://doi.org/10.1080/17483107.2018.1491647
  35. Hallberg, J., Nilsson, M., Synnes, K. (2003). Positioning with Bluetooth. 10th International Conference on Telecommunications, 2003. ICT 2003., 2, pp. 954-958.
  36. Hayashi, T., Ohshige, K., Sawai, A., Yamasue, K., Tochikubo, O. (2008). Seasonal Influence on Blood Pressure in Elderly Normotensive Subjects. Hypertension Research, 31, pp. 569-574. https://doi.org/10.1291/hypres.31.569
  37. He, S., Chan, S. H. G. (2016). Wi-Fi fingerprint-based indoor positioning: Recent advances and comparisons. In IEEE Communications Surveys and Tutorials, 18(1), pp. 466-490. https://doi.org/10.1109/COMST.2015.2464084
  38. Helal, S., Mann, W., El-Zabadani, H., King, J., Kaddoura, Y., Jansen, E. (2005). The Gator Tech Smart House: a programmable pervasive space. Computer, 38(3), pp. 50-60. https://doi.org/10.1109/MC.2005.107
  39. Hong, Y. J., Kim, I. J., Ahn, S. C., Kim, H. G. (2010). Mobile health monitoring system based on activity recognition using accelerometer. Simulation Modelling Practice and Theory, 18(4), pp. 446-455. https://doi.org/10.1016/j.simpat.2009.09.002
  40. Hu, Y., Tilke, D., Adams, T., Crandall, A. S., Cook, D. J., Schmitter-Edgecombe, M. (2016). Smart home in a box: usability study for a large scale self-installation of smart home technologies. Journal of Reliable Intelligent Environments, 2(2), pp. 93-106. https://doi.org/10.1007/s40860-016-0021-y
  41. Huang, W., Xiong, Y., Li, X. Y., Lin, H., Mao, X., Yang, P., Liu, Y. (2014). Shake and walk: Acoustic direction finding and fine-grained indoor localization using smartphones. Proceedings - IEEE INFOCOM, pp. 370-378.
  42. Hupin, D., Roche, F., Gremeaux, V., Chatard, J.-C., Oriol, M., Gaspoz, J.-M., Barthelemy, J.-C., Edouard, P. (2015). Even a low-dose of moderate-to-vigorous physical activity reduces mortality by 22% in adults aged ≥60 years: a systematic review and meta-analysis. British Journal of Sports Medicine, 49(19), pp. 1262-1267. https://doi.org/10.1136/bjsports-2014-094306
  43. Imai, Y., Nishiyama, A., Sekino, M., Aihara, A., Kikuya, M., Ohkubo, T., Matsubara, M., Hozawa, A., Tsuji, I., Ito, S., Satoh, H., Nagai, K., Hisamichi, S. (1999). Characteristics of blood pressure measured at home in the morning and in the evening: the Ohasama study. Journal of Hypertension, 17(7), pp. 889 - 898. https://doi.org/10.1097/00004872-199917070-00004
  44. Inoue, Y. (1996). Longitudinal effects of age on heat-activated sweat gland density and output in healthy active older men. European Journal of Applied Physiology and Occupational Physiology, 74, pp. 72-77. https://doi.org/10.1007/BF00376497
  45. Ishikawa, J., Kario, K., Hoshide, S., Eguchi, K., Morinari, M., Kaneda, R., Umeda, Y., Ishikawa, S., Kuroda, T., Hojo, Y., Shimada, K. (2005). Determinants of exaggerated difference in morning and evening blood pressure measured by self-measured blood pressure monitoring in medicated hypertensive patients: Jichi Morning Hypertension Research (J-MORE) study. American Journal of Hypertension, 18(7), pp. 958-965. https://doi.org/10.1016/j.amjhyper.2005.01.013
  46. Jo, T. H., Ma, J. H., Cha, S. H. (2021). Elderly perception on the internet of things-based integrated smart-home system. Sensors, 21(4), pp. 1-29. https://doi.org/10.1109/JSEN.2020.3039123
  47. Johnston, B., Wheele, L., Deuser, J., Sousa, K. H. (2000). Outcomes of the Kaiser Permanente Tele-Home Health Research Project. Archives of Family Medicine, 9(1), pp. 40-45. https://doi.org/10.1001/archfami.9.1.40
  48. Juvani, S., Isola, A., Kyngas, H. (2005). The northern physical environment and the well-being of the elderly aged over 65 years. International Journal of Circumpolar Health, 64(3), pp. 246-256. https://doi.org/10.3402/ijch.v64i3.17988
  49. Kario, K., Pickering, T. G., Umeda, Y., Hoshide, S., Hoshide, Y., Morinari, M., Murata, M., Kuroda, T., Schwartz, J. E., Shimada, K. (2003). Morning surge in blood pressure as a predictor of silent and clinical cerebrovascular disease in elderly hypertensives: A prospective study. Circulation, 107(10), pp. 1401-1406. https://doi.org/10.1161/01.cir.0000056521.67546.aa
  50. Katz, S. (1983). Assessing self-maintenance: Activities of daily living, mobility, and instrumental activities of daily living. Journal of the American Geriatrics Society, 31(12), pp. 721-727. https://doi.org/10.1111/j.1532-5415.1983.tb03391.x
  51. Kaye, J. A., Maxwell, S. A., Mattek, N., Hayes, T. L., Dodge, H., Pavel, M., Jimison, H. B., Wild, K., Boise, L., Zitzelberger, T. A. (2011). Intelligent Systems For Assessing Aging Changes: home-based, unobtrusive, and continuous assessment of aging. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 66 Suppl 1.
  52. Kekade, S., Hseieh, C. H., Islam, M. M., Atique, S., Mohammed Khalfan, A., Li, Y. C., Abdul, S. S. (2018). The usefulness and actual use of wearable devices among the elderly population. Computer Methods and Programs in Biomedicine, 153, pp. 137-159. https://doi.org/10.1016/j.cmpb.2017.10.008
  53. Kim, J. Y., Liu, N., Tan, H. X., Chu, C. H. (2017). Unobtrusive Monitoring to Detect Depression for Elderly with Chronic Illnesses. IEEE Sensors Journal, 17(17), pp. 5694-5704. https://doi.org/10.1109/JSEN.2017.2729594
  54. KIHASA, Korea Institute for Health and Social Affairs. (2020). 2020 Status of elderly welfare service. Seoul: Ministry of Health and Welfare.
  55. Kim, T. K., Choi, M. (2019). Older adults' willingness to share their personal and health information when adopting healthcare technology and services. International Journal of Medical Informatics, 126, pp. 86-94. https://doi.org/10.1016/j.ijmedinf.2019.03.010
  56. Kohsaka, M., Fukuda, N., Honma, K., Honma, S., Morita, N. (1992). Seasonality in human sleep. Experientia 48, pp. 231-233. https://doi.org/10.1007/BF01930461
  57. Kok, L., Berden, C., Sadiraj, K. (2015). Costs and benefits of home care for the elderly versus residential care: a comparison using propensity scores. European Journal of Health Economics, 16(2), pp. 119-131. https://doi.org/10.1007/s10198-013-0557-1
  58. Kulik, C. T., Ryan, S., Harper, S., George, G. (2014). From the editors: Aging populations and management. Academy of Management Journal, 57(4), pp. 929-935. https://doi.org/10.5465/amj.2014.4004
  59. Lee, B., Lee, H.-S., Park, M. (2018). Behavioral Contextualization for Extracting Occupant's ADL Patterns in Smart-home Environment. Korea Journal of Construction Engineering and Management, 19(1), pp. 21-31. https://doi.org/10.6106/KJCEM.2018.19.1.021
  60. Lee, H., Park, J. W., Helal, A. (2009) Estimation of Indoor Physical Activity Level Based on Footstep Vibration Signal Measured by MEMS Accelerometer in Smart Home Environments. In: Fuller R., Koutsoukos X.D. (eds) Mobile Entity Localization and Tracking in GPS-less Environnments. MELT 2009. Lecture Notes in Computer Science, vol 5801. Springer, Berlin, Heidelberg.
  61. Lee, S. H., Ahn, J. H. (2014). Adoption of the Use of Smart Technology by Health-care Workers in Nursing Homes: an Exploratory Study. Journal of Contents Association, 14(8), pp. 156-171.
  62. Lee, Y. J., Lee, J. H., Nah, J. Y. (2015). Older Adults' Experience of Smart-home Healthcare System. Journal of Korea Contents Association, 15(5), pp. 414-425. https://doi.org/10.5392/JKCA.2015.15.05.414
  63. Lewington, S., Li, L., Sherliker, P., Guo, Y., Millwood, I., Bian, Z., Whitlock, G., Yang, L., Collins, R., Chen, J., Wu, X., Wang, S., Hu, Y., Jiang, L., Yang, L., Lacey, B., Peto, R., Chen, Z. (2012). Seasonal variation in blood pressure and its relationship with outdoor temperature in 10 diverse regions of China: The China Kadoorie Biobank. Journal of Hypertension, 30(7), pp. 1383-1391. https://doi.org/10.1097/hjh.0b013e32835465b5
  64. Li, K. F. (2013). Smart home technology for telemedicine and emergency management. Journal of Ambient Intelligence and Humanized Computing, 4(5), pp. 535-546. https://doi.org/10.1007/s12652-012-0129-8
  65. Lim, D., Park, C., Kim, N. H., Kim, S. H., Yu, Y. S. (2014). Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model. Journal of Applied Mathematics, 2014.
  66. Liu, S., Jiang, Y., Striegel, A. (2014). Face-to-face proximity estimationusing bluetooth on smartphones. IEEE Transactions on Mobile Computing, 13(4), pp. 811-823. https://doi.org/10.1109/TMC.2013.44
  67. Lyons, B. E., Austin, D., Seelye, A., Petersen, J., Yeargers, J., Riley, T., Sharma, N., Mattek, N., Wild, K., Dodge, H., Kaye, J. A. (2015). Pervasive computing technologies to continuously assess Alzheimer's disease progression and intervention efficacy. Frontiers in Aging Neuroscience, 7(JUN).
  68. Madigan, D., Einahrawy, E., Martin, R. P., Wen-Hua Ju, Krishnan, P., Krishnakumar, A. S. (2005). Bayesian indoor positioning systems. Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies., 2, pp. 1217-1227.
  69. Majumder, S., Aghayi, E., Noferesti, M., Memarzadeh-Tehran, H., Mondal, T., Pang, Z., Deen, M. J. (2017). Smart homes for elderly healthcare-Recent advances and research challenges. Sensors, 17(11).
  70. Merchant, A. T., Dehghan, M., Akhtar-Danesh, N. (2007). Seasonal Variation in Leisure-time Physical Activity Among Canadians. Canadian Journal of Public Health, 98(3), pp. 203-208. https://doi.org/10.1007/bf03403713
  71. Miner, B., Kryger, M. H. (2017). Sleep in the Aging Population. Sleep Medicine Clinics, 12(1), pp. 31-38. https://doi.org/10.1016/j.jsmc.2016.10.008
  72. Murphy, S. L., Gretebeck, K. A., Alexander, N. B. (2007). The bath environment, the bathing task, and the older adult: A review and future directions for bathing disability research. Disability and Rehabilitation, 29(14), pp. 1067-1075. https://doi.org/10.1080/09638280600950694
  73. Nag, A., Mukhopadhyay, S. C. (2015). Occupancy Detection at Smart Home Using Real-Time Dynamic Thresholding of Flexiforce Sensor. IEEE Sensors Journal, 15(8), pp. 4457-4463. https://doi.org/10.1109/JSEN.2015.2421348
  74. Ni, H., Wu, S., Abdulrazak, B., Zhang, D., Ma, X., Zhou, X. (2015). Non-intrusive sleep pattern recognition with ubiquitous sensing in elderly assistive environment. Frontiers of Computer Science, 9(6), pp. 966-979. https://doi.org/10.1007/s11704-015-4404-7
  75. Ni, L. M., Liu, Y., Lau, Y. C., Patil, A. P. (2004). LANDMARC: indoor location sensing using active RFID. Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)., 10, pp. 407-415.
  76. Nishinaga, M., Takata, J., Okumiya, K., Matsubayashi, K., Ozawa, T., Doi, Y. (2005). High Morning Home Blood Pressure Is Associated with a Loss of Functional Independence in the Community-Dwelling Elderly Aged 75 Years or Older. Hypertension Research, 28(8), pp. 657-663. https://doi.org/10.1291/hypres.28.657
  77. Ohayon, M. M., Partinen, M. (2002). Insomnia and global sleep dissatisfaction in Finland. Journal of Sleep Research, 11(4), pp. 339-346. https://doi.org/10.1046/j.1365-2869.2002.00317.x
  78. Ohkubo, T., Imai, Y., Tsuji, I., Nagai, K., Kato, J., Kikuchi, N., Nishiyama, A., Aihara, A., Sekino, M., Kikuya, M., Ito, S., Satoh, H., Hisamichi, S. (1988). Home blood pressure measurement has a stronger predictive power for mortality than does screening blood pressure measurement: a population-based observation in Ohasama, Japan. Journal of Hypertension, 16(7), pp. 971-975. https://doi.org/10.1097/00004872-199816070-00010
  79. Okamoto-Mizuno, K., Mizuno, K., Michie, S., Maeda, A., Iizuka, S. (1999). Effects of Humid Heat Exposure on Human Sleep Stages and Body Temperature. Sleep, 22(6).
  80. Okamoto-Mizuno, K., Tsuzuki, K. (2010). Effects of season on sleep and skin temperature in the elderly. International Journal of Biometeorology, 54(4), pp. 401-409. https://doi.org/10.1007/s00484-009-0291-7
  81. Ordonez, F. J., de Toledo, P., Sanchis, A. (2013). Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors. Sensors, 13(5), pp. 5460-5477. https://doi.org/10.3390/s130505460
  82. Owen, N., Healy, G. N., Matthews, C. E., Dunstan, D. W. (2010). Too much sitting: The population health science of sedentary behavior. Exercise and Sport Sciences Reviews, 38(3), pp. 105-113. https://doi.org/10.1097/JES.0b013e3181e373a2
  83. Pal, D., Funilkul, S., Charoenkitkarn, N., Kanthamanon, P. (2018). Internet-of-Things and Smart Homes for Elderly Healthcare: An End User Perspective. IEEE Access, 6, pp. 10483-10496. https://doi.org/10.1109/access.2018.2808472
  84. Palatini, P., Casiglia, E., Julius, S., Pessina, A. C. (1999). High Heart Rate: A Risk Factor for Cardiovascular Death in Elderly Men. Archives of Internal Medicine, 159(6), pp. 585-592. https://doi.org/10.1001/archinte.159.6.585
  85. Pantelopoulos, A., Bourbakis, N. G. (2010). Prognosis-a wearable health-monitoring system for people at risk: Methodology and modeling. IEEE Transactions on Information Technology in Biomedicine, 14(3), pp. 613-621. https://doi.org/10.1109/TITB.2010.2040085
  86. Panza, J. A., Epstein, S. E., Quyyumi, A. A. (1991). Circadian Variation in Vascular Tone and Its Relation to α-Sympathetic Vasoconstrictor Activity. New England Journal of Medicine, 325(14), pp. 986-990. https://doi.org/10.1056/NEJM199110033251402
  87. Peetoom, K. K. B., Lexis, M. A. S., Joore, M., Dirksen, C. D., De Witte, L. P. (2015). Literature review on monitoring technologies and their outcomes in independently living elderly people. Disability and Rehabilitation: Assistive Technology, 10(4), pp. 271-294. https://doi.org/10.3109/17483107.2014.961179
  88. Pol, M., Van Nes, F., Van Hartingsveldt, M., Buurman, B., De Rooij, S., Krose, B. (2016). Older people's perspectives regarding the use of sensor monitoring in their home. Gerontologist, 56(3), pp. 485-493. https://doi.org/10.1093/geront/gnu104
  89. Reeder, B., Chung, J., Lyden, K., Winters, J., Jankowski, C. M. (2020). Older women's perceptions of wearable and smart home activity sensors. Informatics for Health and Social Care, 45(1), pp. 96-109. https://doi.org/10.1080/17538157.2019.1582054
  90. Sakuma, M., Imai, Y., Tsuji, I., Nagai, K., Ohkubo, T., Watanabe, N., Sakuma, H., Satoh, H., Hisamichi, S. (1997). Predictive Value of Home Blood Pressure Measurement in Relation to Stroke Morbidity: A Population-Based Pilot Study in Ohasama, Japan. Hypertension Research, 20(3), pp. 167-174. https://doi.org/10.1291/hypres.20.167
  91. Sanchez, V. G., Pfeiffer, C. F., Skeie, N. O. (2017). A review of smart house analysis methods for assisting older people living alone. Journal of Sensor and Actuator Networks, 6(3).
  92. Schwenk, M., Hauer, K., Zieschang, T., Englert, S., Mohler, J., Najafi, B. (2014). Sensor-derived physical activity parameters can predict future falls in people with dementia. Gerontology, 60(6), pp. 483-492. https://doi.org/10.1159/000363136
  93. Shen, X., Wu, Y., Zhang, D. (2016). Nighttime sleep duration, 24-hour sleep duration and risk of all-cause mortality among adults: A meta-analysis of prospective cohort studies. Scientific Reports, 6.
  94. Sixsmith, A., Johnson, N. (2004). A smart sensor to detect the falls of the elderly. IEEE Pervasive Computing, 3(2), pp. 42-47. https://doi.org/10.1109/MPRV.2004.1316817
  95. Strain, T., Fitzsimons, C., Foster, C., Mutrie, N., Townsend, N., Kelly, P. (2016). Age-related comparisons by sex in the domains of aerobic physical activity for adults in Scotland. Preventive Medicine Reports, 3, pp. 90-97. https://doi.org/10.1016/j.pmedr.2015.12.013
  96. Stucki, R. A., Urwyler, P., Rampa, L., Muri, R., Mosimann, U. P., Nef, T. (2014). A web-based non-intrusive ambient system to measure and classify activities of daily living. Journal of Medical Internet Research, 16(7).
  97. Sucerquia, A., Lopez, J. D., Vargas-Bonilla, J. F. (2018). Real-life/real-time elderly fall detection with a triaxial accelerometer. Sensors, 18(4).
  98. Sumukadas, D., Witham, M., Struthers, A., McMurdo, M. (2009). Day length and weather conditions profoundly affect physical activity levels in older functionally impaired people. Journal of Epidemiology and Community Health, 63(4), pp. 305-309. https://doi.org/10.1136/jech.2008.080838
  99. Togo, F., Watanabe, E., Park, H., Shephard, R. J., Aoyagi, Y. (2005). Meteorology and the physical activity of the elderly: The Nakanojo Study. International Journal of Biometeorology, 50(2), pp. 83-89. https://doi.org/10.1007/s00484-005-0277-z
  100. Tokudome, M., Nagasaki, M., Shimaoka, K., Sato, Y. (2004). Effects of home-based combined resistance training and walking on metabolic profiles in elderly Japanese. Geriatrics and Gerontology International, 4(3), pp. 157-162. https://doi.org/10.1111/j.1447-0594.2004.00241.x
  101. Uitenbroek, D. G. (1993). Seasonal variation in leisure time physical activity. Medicine & Science in Sports & Exercise, 25(6), pp. 755-760. https://doi.org/10.1249/00005768-199306000-00017
  102. Urwyler, P., Stucki, R., Rampa, L., Muri, R., Mosimann, U. P., Nef, T. (2017). Cognitive impairment categorized in community-dwelling older adults with and without dementia using in-home sensors that recognise activities of daily living. Scientific Reports, 7.
  103. Vincent, C., Vincent, C., Routhier, F., Drouin, G., Routhier, F. (2002). Examination of New Environmental Control Applications. Assistive Technology, 14(2), pp. 98-111. https://doi.org/10.1080/10400435.2002.10132059
  104. Wang, J., Katabi, D. (2013). Dude, where's my card? Proceedings of the ACM SIGCOMM 2013 Conference on SIGCOMM, pp. 51-62.
  105. Want, R., Hopper, A., Falcao, V., Gibbons, J. (1992). The active badge location system. ACM Transactions on Information Systems, 10(1), pp. 91-102. https://doi.org/10.1145/128756.128759
  106. Wild, K., Boise, L., Lundell, J., Foucek, A. (2008). Unobtrusive in-home monitoring of cognitive and physical health: Reactions and perceptions of older adults. Journal of Applied Gerontology, 27(2), pp. 181-200. https://doi.org/10.1177/0733464807311435
  107. Wiles, J. L., Leibing, A., Guberman, N., Reeve, J., Allen, R. E. S. (2012). The meaning of "aging in place" to older people. Gerontologist, 52(3), pp. 357-366. https://doi.org/10.1093/geront/gnr098
  108. White, W. B. (2001). Cardiovascular risk and therapeutic intervention for the early morning surge in blood pressure and heart rate. Blood Pressure Monitoring, 6(2), pp. 63-72. https://doi.org/10.1097/00126097-200104000-00001
  109. World Health Organization. (2012). Policies and priority interventions for healthy ageing, https://www.euro.who.int/__data/assets/pdf_file/0006/161637/WHD-Policies-and-Priority-Interventions-for-Healthy-Ageing.pdf (Jul. 17. 2021).
  110. Woodhouse, P. R., Khaw, K. T., Plummer, M. (1993). Seasonal variation of blood pressure and its relationship to ambient temperature in an elderly population. Journal of Hypertension, 11(11), pp. 1267 - 1274.
  111. Xie, H., Gu, T., Tao, X., Ye, H., Lv, J. (2014). MaLoc: A practical magnetic fingerprinting approach to indoor localization using sma rtphones. UbiComp 2014 - Proceedings of the 2014 ACM Inte rnational Joint Conference on Pervasive and Ubiquitous Computing, pp. 243-253.
  112. Yamamoto, N., Miyazaki, H., Shimada, M., Nakagawa, N., Sawada, S. S., Nishimuta, M., Kimura, Y., Kawakami, R., Nagayama, H., Asai, H., Lee, I. M., Blair, S. N., Yoshitake, Y. (2018). Daily step count and all-cause mortality in a sample of Japanese elderly people: A cohort study. BMC Public Health, 18(1).
  113. Zhu, N., Diethe, T., Camplani, M., Tao, L., Burrows, A., Twomey, N., Kaleshi, D., Mirmehdi, M., Flach, P., Craddock, I. (2015). Bridging e-Health and the Internet of Things: The SPHERE Project. IEEE Intelligent Systems, 30(4), pp. 39-46. https://doi.org/10.1109/MIS.2015.57